This contribution develops and implements INDISIM-Saccha, a spatially explicit IBM model to analyze the dynamics of Saccharomyces cerevisiae anaerobic cultures evolving in a liquid medium with glucose as a main carbon source and organic and inorganic nitrogen sources. The model has been parameterized, calibrated and its adequacy assessed using available experimental data. The growth of the yeast population and the glucose depletion were simulated, and changes in the ethanol production kinetics r...

This contribution develops and implements INDISIM-Saccha, a spatially explicit IBM model to analyze the dynamics of Saccharomyces cerevisiae anaerobic cultures evolving in a liquid medium with glucose as a main carbon source and organic and inorganic nitrogen sources. The model has been parameterized, calibrated and its adequacy assessed using available experimental data. The growth of the yeast population and the glucose depletion were simulated, and changes in the ethanol production kinetics resulting from differences in the size distribution of the cells making up the inocula were examined in silico. Uncertainty on the initial estimated values of the model parameters was reduced by means of an iterative process involving a computational full factorial experiment, and the parameter values reproducing simultaneously glucose depletion and growth curves of batch cultures in two initial glucose concentrations were selected. The model adequacy was assessed with multiple both individual and population patterns not previously used in the calibration process carried out. Three virtual experiments were conducted from inocula with different cell size distributions. The maximum yeast cell number, the specific growth rate and the time to achieve the maximum ethanol produced were studied. Although the ethanol obtained was similar in the three studied situations, the time required to achieve it was significantly different, fermentations started by inocula made up of greater cells showed increased productivity. Due to the importance of S. cerevisiae in both fundamental research and industrial production contexts, having a calibrated computational model capable of studying the structures of this yeast population and the profiles of the fermentations carried out by it represents a noteworthy advancement in the field of microbial ecology. (C) 2014 Elsevier B.V. All rights reserved.